Eigenmotion-Based Detection of Intestinal Contractions

Intestinal contractions are one of the main features for analyzing intestinal motility and detecting different gastrointestinal pathologies. In this paper we propose Eigenmotion-based Contraction Detection (ECD), a novel approach for automatic annotation of intestinal contractions of video capsule endoscopy. Our approach extracts the main motion information of a set of contraction sequences in form of eigenmotions using Principal Component Analysis. Then, it uses a selection of them to represent the high dimension motion data. Finally, this contraction characterization is used to classify the contraction sequences by means of machine learning techniques. The experimental results show that motion information is useful in the contraction detection. Moreover, the proposed automatic method is essential to speed up the costly examination of the video capsule endoscopy.